PsyAttention: Psychological Attention Model for Personality Detection
December 01, 2023 ยท Declared Dead ยท ๐ Conference on Empirical Methods in Natural Language Processing
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Authors
Baohua Zhang, Yongyi Huang, Wenyao Cui, Huaping Zhang, Jianyun Shang
arXiv ID
2312.00293
Category
cs.CL: Computation & Language
Citations
6
Venue
Conference on Empirical Methods in Natural Language Processing
Last Checked
5 months ago
Abstract
Work on personality detection has tended to incorporate psychological features from different personality models, such as BigFive and MBTI. There are more than 900 psychological features, each of which is helpful for personality detection. However, when used in combination, the application of different calculation standards among these features may result in interference between features calculated using distinct systems, thereby introducing noise and reducing performance. This paper adapts different psychological models in the proposed PsyAttention for personality detection, which can effectively encode psychological features, reducing their number by 85%. In experiments on the BigFive and MBTI models, PysAttention achieved average accuracy of 65.66% and 86.30%, respectively, outperforming state-of-the-art methods, indicating that it is effective at encoding psychological features.
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